Advanced Process Control

Advanced Process Control

nptelhrd via YouTube Direct link

Multivariable Decoupling Control and Soft Sensing and State Estimation

16 of 26

16 of 26

Multivariable Decoupling Control and Soft Sensing and State Estimation

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Classroom Contents

Advanced Process Control

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  1. 1 Introduction and Motivation
  2. 2 Linearization of Mechanistic Models
  3. 3 Linearization of Mechanistic Models (Contd.)
  4. 4 Introduction to z-transforms and Development of Grey-box models
  5. 5 Introduction to Stability Analysis and Development of Output Error Models
  6. 6 Introduction to Stochastic Processes
  7. 7 Introduction to Stochastic Processes (Contd.)
  8. 8 Development of ARX models
  9. 9 Statistical Properties of ARX models and Development of ARMAX models
  10. 10 Development of ARMAX models (contd.) and Issues in Model Development
  11. 11 Model Structure Selection and Issues in Model Development (contd.)
  12. 12 Issues in Model Development (contd.) and State Realizations of Transfer Function Models
  13. 13 Stability Analysis of Discrete Time Systems
  14. 14 Lyapunov Functions and Interaction Analysis and Multi-loop Control
  15. 15 Interaction Analysis and Multi-loop Control (contd.)
  16. 16 Multivariable Decoupling Control and Soft Sensing and State Estimation
  17. 17 Development of Luenberger Observer
  18. 18 Development of Luenberger Observer (contd.) and Introduction to Kalman Filtering
  19. 19 Kalman Filtering
  20. 20 Kalman Filtering (contd.)
  21. 21 Kalman Filtering (contd.)
  22. 22 Pole Placement State Feedback Control Design and Introduction to Linear Quadratic Gaussian Control
  23. 23 Linear Quadratic Gaussian (LQG) Regulator Design
  24. 24 Linear Quadratic Gaussian (LQG) Controller Design
  25. 25 Model Predictive Control (MPC)
  26. 26 Model Predictive Control (contd.)

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